Research Assistant in GeoAI, GIS and Urban Flood Resilience at NUS, Singapore

The National University of Singapore (NUS) advertised a Research Assistant position focused on GeoAI, Geographic Information Systems (GIS), and Urban Flood Resilience. The opportunity was associated with a research project investigating how geospatial data and artificial intelligence can help assess urban flood resilience in Southeast Asia.

The position was based at NUS’s Kent Ridge Campus and involved interdisciplinary research connecting geography, architecture, urban analytics, climate resilience, and disaster risk management.

Important status update: The advertised application deadline was 20 October 2026. The project’s official Urban Analytics Lab vacancy page now states that applications are closed. As of 22 October 2026, this opportunity should be treated as closed unless NUS announces that applications have reopened.

Job Overview

• Position: Research Assistant (GeoAI / GIS / Urban Flood Resilience)
• Institution: National University of Singapore (NUS)
• Research Group: Urban Analytics Lab
• Academic Unit: Department of Geography, Faculty of Arts and Social Sciences
• Location: Kent Ridge Campus, Singapore
• Employment Type: Research staff, full-time
• Project Duration: One year
• Expected Start Date: January 2027
• Application Deadline: 20 October 2026 — closed
• Official Job Reference: 34646

About the Research Project

The research project, titled “Assessing Urban Flood Resilience against Climate Extreme with GeoAI in Southeast Asia,” aims to develop a GeoAI-based framework for evaluating urban flood risk and resilience.

The project combines multiple sources of geospatial information, including GIS datasets, remote-sensing imagery, street-view imagery, and socio-demographic data. By integrating these sources with artificial intelligence and machine-learning methods, the research seeks to support a better understanding of flood resilience across Southeast Asian cities.

The position is relevant to researchers interested in geospatial technologies, data-driven urban planning, climate adaptation, disaster risk reduction, and the application of computational methods to built-environment challenges.

Key Responsibilities

The selected Research Assistant would contribute to the following activities:

• Process, integrate, and analyse multimodal geospatial datasets.
• Develop and evaluate GeoAI and machine-learning methods for mapping urban flood risk and resilience.
• Conduct spatial and statistical analyses using Python, R, and GIS tools.
• Produce visualisations and support comparative research across Southeast Asian cities.
• Conduct literature reviews and contribute to research publications and project reports.
• Collaborate with the principal investigator, co-investigator, and student researchers.
• Assist with project management, administrative activities, and funding applications.

Eligibility and Qualifications

Applicants were expected to hold a Bachelor’s or Master’s degree in one of the following fields or a related discipline:

• Geography or GIScience
• Geomatics
• Remote Sensing
• Computer Science
• Data Science
• Urban Planning

Candidates were also expected to demonstrate:

• Strong GIS and spatial-analysis skills.
• Programming experience in Python and/or R.
• Experience processing and visualising geospatial data.
• Strong analytical, communication, and academic-writing skills.

Knowledge of GeoAI, machine learning, deep learning, or computer vision was desirable. Experience in urban climate, flooding, disaster risk, remote sensing, or urban analytics was considered an advantage.

This was described as an entry-level position. Applicants with research experience, publications, or evidence of relevant technical work, such as a developed code repository, were expected to receive priority consideration. Candidates did not need expertise in every listed area; a strong foundation in geospatial analysis and programming was encouraged.

Salary and Benefits

The remuneration was to be determined according to the university’s salary range, depending on the candidate’s qualifications and experience. The published notice did not specify a fixed salary.

The advertised opportunity offered experience in an interdisciplinary research environment, collaboration with researchers and students, exposure to emerging GeoAI technologies, and the opportunity to develop a research portfolio in climate resilience and disaster management.

Work Location and Duration

The position was based at the main campus of the National University of Singapore at Kent Ridge, Singapore. The role was explicitly identified as an on-site position, not a remote job.

The appointment was planned for one year, with an expected start in January 2027.

Application Procedure

The original recruitment notice directed applicants to apply through the NUS Careers portal. The application materials were to include a CV and could also include a portfolio, cover letter, or other relevant supporting material, preferably in PDF format. Applicants were also asked to provide consent for the collection, use, and disclosure of personal data through the university’s Personal Data Consent for Job Applicants form.

Applications are currently closed. The deadline was 20 October 2026, and the Urban Analytics Lab has confirmed that it is no longer accepting applications for this position.

Candidates interested in similar opportunities can monitor the NUS Careers website and the Urban Analytics Lab’s vacancies page for future research openings.

Official Links

• Urban Analytics Lab Vacancy Notice: https://ual.sg/opportunities/ads/2026-ra/
• Urban Analytics Lab Opportunities: https://ual.sg/opportunities/